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Model Selection Bas...
Model Selection Based Algorithm in Neonatal Chest EIT
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- Seifnaraghi, Nima (författare)
- Middlesex University, UK
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- de Gelidi, Serena (författare)
- Middlesex University, UK
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- Nordebo, Sven, 1963- (författare)
- Linnéuniversitetet,Institutionen för fysik och elektroteknik (IFE)
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- Kallio, Merja (författare)
- University of Oulu, Finland;Oulu University Hospital, Finland
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- Frerichs, Inez (författare)
- University Medical Centre Schleswig-Holstein, Germany
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- Tizzard, Andrew (författare)
- Middlesex University, UK
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- Suo-Palosaari, Maria (författare)
- University of Oulu, Finland;Oulu University Hospital, Finland
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- Sophocleous, Louiza (författare)
- University of Cyprus, Cyprus
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- van Kaam, Anton H. (författare)
- Amsterdam University Medical Centres, Neherlands
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- Sorantin, Erich (författare)
- Medical University of Graz, Austria
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- Demosthenous, Andreas (författare)
- University College London, UK
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- Bayford, Richard H. (författare)
- Middlesex University, UK
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(creator_code:org_t)
- IEEE, 2021
- 2021
- Engelska.
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Ingår i: IEEE Transactions on Biomedical Engineering. - : IEEE. - 0018-9294 .- 1558-2531. ; 68:9, s. 2752-2763
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- This paper presents a new method for selecting a patient specific forward model to compensate for anatomical variations in electrical impedance tomography (EIT) monitoring of neonates. The method uses a combination of shape sensors and absolute reconstruction. It takes advantage of a probabilistic approach which automatically selects the best estimated forward model fit from pre-stored library models. Absolute/static image reconstruction is performed as the core of the posterior probability calculations. The validity and reliability of the algorithm in detecting a suitable model in the presence of measurement noise is studied with simulated and measured data from 11 patients. The paper also demonstrates the potential improvements on the clinical parameters extracted from EIT images by considering a unique case study with a neonate patient undergoing computed tomography imaging as clinical indication prior to EIT monitoring. Two well-known image reconstruction techniques, namely GREIT and tSVD, are implemented to create the final tidal images. The impacts of appropriate model selection on the clinical extracted parameters such as center of ventilation and silent spaces are investigated. The results show significant improvements to the final reconstructed images and more importantly to the clinical EIT parameters extracted from the images that are crucial for decision-making and further interventions.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
Nyckelord
- Tomography
- Pediatrics
- Electrodes
- Imaging
- Conductivity
- Image reconstruction
- Lung
- Electrical impedance tomography
- model selection
- neonatal chest EIT
- patient-specific prior model
- thorax modelling
- Electrotechnology
- Elektroteknik alt Electrical engineering
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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Till lärosätets databas
- Av författaren/redakt...
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Seifnaraghi, Nim ...
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de Gelidi, Seren ...
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Nordebo, Sven, 1 ...
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Kallio, Merja
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Frerichs, Inez
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Tizzard, Andrew
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visa fler...
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Suo-Palosaari, M ...
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Sophocleous, Lou ...
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van Kaam, Anton ...
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Sorantin, Erich
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Demosthenous, An ...
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Bayford, Richard ...
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Linnéuniversitetet